Image Reconstruction in Electrical Impedance Tomography (EIT) with Projection Error Propagation-based Regularization (PEPR): A Practical Phantom Study

Resistivity reconstruction of practical phantoms is studied with Projection Error Propagation-based Regularization (PEPR) method to improve the image quality in Electrical Impedance Tomography (EIT). PEPR method calculates the regularization parameter as a function of the projection error produced due to the mismatch between experimental measurements and the calculated data. The regularization parameter in the reconstruction algorithm automatically adjusts its magnitude depending on the noise level present in measured data as well as the ill-posedness of the Hessian matrix. Resistivity images are reconstructed from the practical phantom data using the Electrical Impedance Diffuse Optical Reconstruction Software (EIDORS). The resistivity images reconstructed with PEPR method are compared with the Single step Tikhonov Regularization (STR) and Modified Levenberg Regularization (LMR) techniques. The results show that, the PEPR technique reduces the reconstruction errors in each iteration and improves the reconstructed images with better contrast to noise ratio (CNR), percentage of contrast recovery (PCR), coefficient of contrast (COC) and diametric resistivity profile (DRP).

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